Create app.py

app.py

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+import os
+import streamlit as st
+from PIL import Image
+import datetime
+
+# Folder paths
+INPUT_FOLDER = "./input/"
+OUTPUT_FOLDER = "./output/"
+LOG_FOLDER = "./logs/"
+PROCESSED_IMAGE = os.path.join(OUTPUT_FOLDER, "processed_image.png")
+
+# Ensure required folders exist
+os.makedirs(INPUT_FOLDER, exist_ok=True)
+os.makedirs(OUTPUT_FOLDER, exist_ok=True)
+os.makedirs(LOG_FOLDER, exist_ok=True)
+
+# Function to log conversion steps
+def log_conversion(status, input_image, output_image):
+    log_path = os.path.join(LOG_FOLDER, "conversion_log.txt")
+    with open(log_path, "a") as log_file:
+        log_file.write(f"{datetime.datetime.now()} - Status: {status}\n")
+        log_file.write(f"Input Image: {input_image}\n")
+        log_file.write(f"Output Image: {output_image}\n\n")
+
+# Streamlit app interface
+def main():
+    st.title("Image Grayscale Converter and Resizer")
+
+    # File upload
+    uploaded_file = st.file_uploader("Upload your image file", type=["jpg", "jpeg", "png"])
+    if uploaded_file:
+        input_image_path = os.path.join(INPUT_FOLDER, uploaded_file.name)
+        with open(input_image_path, "wb") as f:
+            f.write(uploaded_file.read())
+        st.success(f"File uploaded: {uploaded_file.name}")
+
+        # Display the uploaded image
+        st.image(input_image_path, caption="Uploaded Image", use_column_width=True)
+
+        # User controls for adjustments
+        new_width = st.number_input("Width (pixels)", value=800, step=10)
+        new_height = st.number_input("Height (pixels)", value=600, step=10)
+
+        # Process the file
+        if st.button("Process Image"):
+            try:
+                # Step 1: Open and process the image
+                with Image.open(input_image_path) as img:
+                    grayscale_image = img.convert("L")  # Convert to grayscale
+                    resized_image = grayscale_image.resize((new_width, new_height))  # Resize
+                    resized_image.save(PROCESSED_IMAGE)
+
+                # Step 2: Log the process
+                log_conversion("Success", input_image_path, PROCESSED_IMAGE)
+
+                # Provide download link
+                st.success("Image processed successfully!")
+                st.image(PROCESSED_IMAGE, caption="Processed Image", use_column_width=True)
+                st.download_button("Download Processed Image", open(PROCESSED_IMAGE, "rb"), file_name="processed_image.png")
+            except Exception as e:
+                log_conversion("Failed", input_image_path, PROCESSED_IMAGE)
+                st.error(f"Error processing image: {e}")
+
+if __name__ == "__main__":
+    main()